System and method for efficiently performing a white balance operation

ABSTRACT

A system and method for efficiently performing a white balance operation preferably includes an electronic camera device that captures image data using a imaging device. A color manager may then convert the captured image data into perceptual color space data. The color manager may next create a histogram of chromaticity vectors corresponding to pixels from the perceptual color space data. The color manager may then derive a neutral core vector corresponding to a neutral core peak from the histogram. The color manager may advantageously utilize the neutral core vector to identify a scene illuminant corresponding to color channel amplifier gains, and may then adjust the captured image data with the color channel amplifier gains to thereby complete the white balance operation.

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application relates to, and claims priority in, U.S.Provisional Pat. App. Ser. No. 60/312,626, entitled “PerformIllumination Estimation From Raw Data By Using The Neutral Core OfPixels In A Perceptual Space” that was filed on Aug. 15, 2001. Therelated applications are commonly assigned.

BACKGROUND SECTION

[0002] 1. Field of the Invention

[0003] This invention relates generally to techniques for manipulatingdata, and relates more particularly to a system and method forefficiently performing a white balance operation in the field of digitalimaging.

[0004] 2. Description of the Background Art

[0005] Implementing efficient methods for manipulating data is asignificant consideration for designers and manufacturers ofcontemporary electronic devices. However, effectively manipulating datawith electronic devices may create substantial challenges for systemdesigners. For example, enhanced demands for increased devicefunctionality and performance may require more system processing powerand require additional hardware resources. An increase in processing orhardware requirements may also result in a corresponding detrimentaleconomic impact due to increased production costs and operationalinefficiencies.

[0006] Furthermore, enhanced device capability to perform variousadvanced operations may provide additional benefits to a system user,but may also place increased demands on the control and management ofvarious device components. For example, an enhanced electronic devicethat efficiently captures and manipulates digital image data may benefitfrom an efficient implementation because of the large amount andcomplexity of the digital data involved.

[0007] In certain electronic cameras that capture digital image data, awhite balancing operation may be required. In practice, the human visualsystem does not perceive the same amount of light and the same colorsthat an electronic camera captures as image data. White balancingoperations therefore adjust the image data captured by the electroniccamera, so that a resultant captured image appears the same as the imagethat was originally perceived by the human eye.

[0008] Due to growing demands on system resources and substantiallyincreasing data magnitudes, it is apparent that developing newtechniques for manipulating data is a matter of concern for relatedelectronic technologies. Therefore, for all the foregoing reasons,developing efficient systems for manipulating data remains a significantconsideration for designers, manufacturers, and users of contemporaryelectronic devices.

SUMMARY

[0009] In accordance with the present invention, a system and method aredisclosed for efficiently performing a white balance operation. In oneembodiment, initially, an electronic camera device generates capturedimage data using a imaging device. A color manager or other appropriateentity may then preferably decimate the pixels of captured image data toreduce the overall number of pixels by utilizing any appropriate andeffective technique. For example, the color manager may exclude every“nth” pixel from the capture image data. In certain embodiments, pixelswith values under a predetermined threshold value may also beeliminated.

[0010] The color manager or other appropriate entity may next preferablyconvert the foregoing decimated pixels into a perceptual color space.For example, the color manager may convert the decimated pixels into athree-dimensional perceptual color space that includes one luminancecoordinate and two color coordinates, such as the L*a*b* color space, orinto any other suitable and effective color space.

[0011] The color manager or other appropriate entity may then preferablycalculate chromaticity vectors for each pixel from the perceptual colorspace, and may also preferably group the foregoing chromaticity vectorsinto a series of contiguous theta bins that may be presented as ahistogram with one or more peaks each corresponding to total counts ofthe chromaticity vectors in the foregoing theta bins. In this context,“theta bins” refer to a measure of a pixel's hue range over the colorsof the rainbow. Typically, the range is red, orange, yellow, green,blue, indigo, and violet. However, the starting point for the foregoingcolor sequence may not be critical.

[0012] The color manager or other appropriate entity may preferablyidentify a neutral core peak from the histogram by utilizing anyeffective techniques. For example, in certain embodiments, the colormanager may preferably identify the foregoing neutral core peak as the“blue-est” peak in the blue region of the theta bins from the histogramthat possess sufficient count amplitude and luminance range.

[0013] The color manager or other appropriate entity may preferably alsoderive a neutral core vector from data values corresponding to theforegoing neutral core peak by utilizing any appropriate techniques. Forexample, in certain embodiments, the color manager may preferablycalculate averages of L*, a*, and b* values for all chromaticity vectorsin the theta bin(s) that correspond to the neutral core peak to therebydetermine L*a*b* coordinates of the neutral core vector.

[0014] The color manager or other appropriate entity may then preferablycompare the neutral core vector with reference vectors from variousknown standard illuminants to identify the scene illuminantcorresponding to the captured image data. Finally, the color manager orother appropriate entity may preferably access color amplifier gains forprimary color channels of the camera device based upon the identifiedscene illuminant by using any appropriate means. For example, the colormanager may reference one or more lookup tables with the identifiedscene illuminant to determine the correct color amplifier gains for thatilluminant.

[0015] The color manager or other appropriate entity may then preferablyutilize the referenced color amplifier gains to adjust the gains ofprimary color channels in the camera device, to thereby complete thewhite balance operation in accordance with the present invention. Thepresent invention thus provides an improved system and method forefficiently performing a white balance operation.

BRIEF DESCRIPTION OF THE DRAWINGS

[0016]FIG. 1 is a block diagram for one embodiment of a camera device,in accordance with the present invention;

[0017]FIG. 2 is a block diagram for one embodiment of the capturesubsystem of FIG. 1, in accordance with the present invention;

[0018]FIG. 3 is a block diagram for one embodiment of the control moduleof FIG. 1, in accordance with the present invention;

[0019]FIG. 4 is a block diagram for one embodiment of the memory of FIG.3, in accordance with the present invention;

[0020]FIG. 5 is a block diagram for one embodiment of the red, green,and blue amplifiers of FIG. 2, in accordance with the present invention;

[0021]FIG. 6 is a graph illustrating a chromaticity vector inthree-dimensional perceptual color space, in accordance with the presentinvention;

[0022]FIG. 7 is a graph of an exemplary histogram, in accordance withone embodiment of the present invention;

[0023]FIG. 8 is a graph illustrating a neutral core vector and tworeference vectors in three-dimensional perceptual color space, inaccordance with the present invention;

[0024]FIG. 9 is a flowchart of method steps for performing a basicneutral-core white-balance operation, in accordance with one embodimentof the present invention; and

[0025] FIGS. 10A-B are a flowchart of method steps for performing adetailed neutral-core white-balance operation, in accordance with oneembodiment of the present invention.

DETAILED DESCRIPTION

[0026] The present invention relates to an improvement in datamanipulation techniques. The following description is presented toenable one of ordinary skill in the art to make and use the inventionand is provided in the context of a patent application and itsrequirements. Various modifications to the disclosed embodiments will bereadily apparent to those skilled in the art, and the generic principlesherein may be applied to other embodiments. Thus, the present inventionis not intended to be limited to the embodiments shown, but is to beaccorded the widest scope consistent with the principles and featuresdescribed herein.

[0027] The present invention comprises a system and method forefficiently performing a white balance operation, and preferablyincludes an electronic camera device that captures image data using aimaging device. A color manager may then convert the captured image datainto perceptual color space data. The color manager may next create ahistogram of chromaticity vectors corresponding to pixels from theperceptual color space data. The color manager may derive a neutral corevector corresponding to a neutral core peak from the histogram. Thecolor manager may advantageously utilize the neutral core vector toidentify a scene illuminant corresponding to color channel amplifiergains, and may then adjust the captured image data with the colorchannel amplifier gains to thereby complete the white balance operation.

[0028] Referring now to FIG. 1, a block diagram for one embodiment of acamera device 110 is shown, in accordance with the present invention. Inthe FIG. 1 embodiment, camera device 110 may include, but is not limitedto, a capture subsystem 114, a system bus 116, and a control module 118.In the FIG. 1 embodiment, capture subsystem 114 may be optically coupledto a target object 112, and may also be electrically coupled via systembus 116 to control module 118.

[0029] In alternate embodiments, camera device 110 may readily includevarious other components in addition to, or instead of, those componentsdiscussed in conjunction with the FIG. 1 embodiment. In addition, incertain embodiments, the present invention may alternately be embodiedin any appropriate type of electronic device other than the cameradevice 110 of FIG. 1. For example, camera device 110 may readily beimplemented as a scanner device or a video camera device.

[0030] In the FIG. 1 embodiment, once a system user has focused capturesubsystem 114 on target object 112 and requested camera device 110 tocapture image data corresponding to target object 112, then controlmodule 118 may preferably instruct capture subsystem 114 via system bus116 to capture image data representing target object 112. The capturedimage data may then be transferred over system bus 116 to control module118, which may responsively perform various processes and functions withthe image data. System bus 116 may also bidirectionally pass variousstatus and control signals between capture subsystem 114 and controlmodule 118.

[0031] Referring now to FIG. 2, a block diagram for one embodiment ofthe FIG. 1 capture subsystem 114 is shown, in accordance with thepresent invention. In the FIG. 2 embodiment, imaging device 114preferably comprises, but is not limited to, a lens 220 having an iris(not shown), a filter 222, an image sensor 224, a timing generator 226,red, green, and blue amplifiers 228, an analog-to-digital (A/D)converter 230, an interface 232, and one or more motors 234 to adjustthe focus of lens 220. In alternate embodiments, capture subsystem 114may readily include various other components in addition to, or insteadof, those components discussed in conjunction with the FIG. 2embodiment.

[0032] In the FIG. 2 embodiment, capture subsystem 114 may preferablycapture image data corresponding to target object 112 via reflectedlight impacting image sensor 224 along optical path 236. Image sensor224, which may preferably include a charged-coupled device (CCD), mayresponsively generate a set of image data representing the target object112. The image data may then be routed through red, green, and blueamplifiers 228, A/D converter 230, and interface 232. Interface 232 maypreferably include separate interfaces for controlling ASP 228, motors234, timing generator 226, and red, green, and blue amplifiers 228. Frominterface 232, the image data passes over system bus 116 to controlmodule 118 for appropriate processing and storage. Other types of imagecapture sensors, such as CMOS or linear arrays are also contemplated forcapturing image data in conjunction with the present invention. Forexample, the image capture sensors preferably include three or moreprimary color channels (for example, Cyan/Magenta/Yellow/Green (C/M/Y/G)is also considered).

[0033] Referring now to FIG. 3, a block diagram for one embodiment ofthe FIG. 1 control module 118 is shown, in accordance with the presentinvention. In the FIG. 3 embodiment, control module 118 preferablyincludes, but is not limited to, a viewfinder 308, a central processingunit (CPU) 344, a memory 346, and one or more input/output interface(s)(I/O) 348. Viewfinder 308, CPU 344, memory 346, and I/O 348 preferablyare each coupled to, and communicate, via common system bus 116 thatalso communicates with capture subsystem 114. In alternate embodiments,control module 118 may readily include various other components inaddition to, or instead of, those components discussed in conjunctionwith the FIG. 3 embodiment.

[0034] In the FIG. 3 embodiment, CPU 344 may preferably be implementedto include any appropriate microprocessor device. Alternately, CPU 344may be implemented using any other appropriate technology. For example,CPU 344 may be implemented to include certain application-specificintegrated circuits (ASICS) or other appropriate electronic devices.Memory 346 may preferably be implemented as one or more appropriatestorage devices, including, but not limited to, read-only memory,random-access memory, and various types of non-volatile memory, such asfloppy disc devices, hard disc devices, or flash memory. I/O 348preferably may provide one or more effective interfaces for facilitatingbi-directional communications between camera device 110 and any externalentity, including a system user or another electronic device. I/O 348may be implemented using any appropriate input and/or output devices.The operation and utilization of control module 118 is further discussedbelow in conjunction with FIGS. 4 through 11.

[0035] Referring now to FIG. 4, a block diagram for one embodiment ofthe FIG. 3 memory 346 is shown, in accordance with the presentinvention. In the FIG. 4 embodiment, memory 346 may preferably include,but is not limited to, a camera application 412, an operating system414, a color manager 416, raw image data 418, final image data 420,white balance information 422, and miscellaneous information 424. Inalternate embodiments, memory 346 may readily include various othercomponents in addition to, or instead of, those components discussed inconjunction with the FIG. 4 embodiment.

[0036] In the FIG. 4 embodiment, camera application 412 may includeprogram instructions that are preferably executed by CPU 344 (FIG. 3) toperform various functions and operations for camera device 110. Theparticular nature and functionality of camera application 412 preferablyvaries depending upon factors such as the type and particular use of thecorresponding camera device 110.

[0037] In the FIG. 4 embodiment, operating system 414 preferablycontrols and coordinates low-level functionality of camera device 110.In accordance with the present invention, color manager 416 maypreferably control and coordinate a white balance operation for imagedata 422 captured by camera device 110. The functionality of colormanager 416 is further discussed below in conjunction with FIGS. 6through 10D.

[0038] In the FIG. 4 embodiment, color manager 416 may preferablyutilize raw image data 418 to perform a white balance operation tothereby produce final image data 420. White balance information 422 maypreferably include any appropriate information or data that is utilizedduring the foregoing white balance operation. Miscellaneous information424 may include any desired software instructions, data, or otherinformation for facilitating various functions performed by cameradevice 110.

[0039] Referring now to FIG. 5, a block diagram of the FIG. 2 red,green, and blue amplifiers 228 is shown, in accordance with oneembodiment of the present invention. In alternate embodiments of thepresent invention, red, green, and blue amplifiers 228 may readily beimplemented to include various other configurations, and may alsoinclude various items and components that are different from thosediscussed in conjunction with the FIG. 5 embodiment. For example, incertain embodiments, red, green, and blue amplifiers 228 may readily beimplemented in other locations in camera device 110, such as followingA/D converter 230 or within the capture device itself.

[0040] In the FIG. 5 embodiment, image sensor 224 may preferablygenerate a red sensor output to a red amplifier 228(a) which mayresponsively provide an amplified red output to A/D converter 230. Redamplifier 228(a) may preferably adjust the signal amplitude of the redsensor output according to a red amplification value referred to hereinas red gain. Similarly, image sensor 224 may preferably generate a greensensor output to a green amplifier 228(b) which may responsively providean amplified green output to A/D converter 230. Green amplifier 228(b)may preferably adjust the signal amplitude of the green sensor outputaccording to a green amplification value referred to herein as greengain.

[0041] In addition, image sensor 224 may preferably generate a bluesensor output to a blue amplifier 228(c) which may responsively providean amplified blue output to A/D converter 230. Blue amplifier 228(c) maypreferably adjust the signal amplitude of the blue sensor outputaccording to a blue amplification value referred to herein as blue gain.In accordance with the present invention, image sensor 224 may beimplemented using any appropriate image capture technology. Improvedtechniques for adjusting the respective gains of red, green, and blueamplifiers 428 in order to achieve an appropriate white balance forcurrent lighting conditions is further discussed below in conjunctionwith FIGS. 6 through 10D.

[0042] Referring now to FIG. 6, a graph illustrating a chromaticityvector 734 in three-dimensional perceptual color space 610 is shown, inaccordance with one embodiment of the present invention. In alternateembodiments, the present invention may readily utilize chromaticityvectors 610 that are implemented in various other color spaces (such asLuv or HSV), and may also include various items and configurations thatare different from those discussed in conjunction with the FIG. 6embodiment.

[0043] In the FIG. 6 embodiment, perceptual color space 610 maypreferably be implemented as a conventional L*a*b* color-spacerepresentation with a horizontal “a*” axis 618 (green to magenta), ahorizontal “b*” axis 622 (yellow to blue), and a vertical luminance L*axis 614. The FIG. 6 embodiment also includes an exemplary chromaticityvector 634 that corresponds to a particular pixel. Also shown is a phiangle 626 which is the declination angle of chromaticity vector 634 fromL* axis 614. The FIG. 6 embodiment also includes a theta angle 630corresponding to chromaticity vector 634. Theta angle 630 preferablydescribe the angle of chromaticity vector 634 from a* axis 618 in thesame plane as a* axis 618 and b* axis 622.

[0044] A goal of the present invention is illuminant estimation (IE) ofcaptured image data to determine the relative gains of the primary coloramplifiers 228 needed for this particular illuminant. The presentinvention requires selected L*a*b* pixels to be histogrammed. Thehistogram variable is theta 630 which is preferably equal to theArcTan(b*/a*). Theta may be considered to be the hue of chromaticityvector 634. In this embodiment, theta is the hue (chromaticity) angledefined in the CIE L*a*b* procedures. It represents a cyclical variablethat describes what color the L*a*b* pixel refers to in a uniformperceptual color space. While the angle theta 630 shows what “color” apixel refers to, the phi angle 626 gives an indication of how saturatedthe same given pixel is.

[0045] The present invention may then preferably divide the circularplane of a* 618 and b* 622 into a number of contiguous theta bins. Inthe FIG. 6 embodiment, approximately 158 theta bins may preferably beutilized. However, in other embodiments, any appropriate and effectivenumber of theta bins may be utilized. A chromaticity vector 634 for eachselected pixel from image data in the perceptual color space may then becalculated. A separate “count” for each chromaticity vector 634 may thenbe assigned to the appropriate theta bin, depending upon the theta valueof the corresponding chromaticity vector 634. In accordance with thepresent invention, the counts in the foregoing theta bins may then beconverted into a histogram, as discussed below in conjunction with FIG.7.

[0046] Referring now to FIG. 7, a graph of an exemplary histogram 710 isshown, in accordance with one embodiment of the present invention. Thehistogram 710 of FIG. 7 is presented for purposed of illustration, andin alternate embodiments of the present invention, histogram 710 mayreadily include other coordinates and waveforms in variousconfigurations that are different from those discussed in conjunctionwith the FIG. 7 embodiment.

[0047] In the FIG. 7 example, the horizontal axis 718 of histogram 710may preferably display reference numbers corresponding to the contiguoustheta bins discussed above in conjunction with FIG. 6. In addition, inthe FIG. 7 embodiment, the vertical axis 714 of histogram 710 maypreferably display the number of “counts” (a total number ofchromaticity vectors 634 assigned to the various theta bins for a givencaptured image) as discussed above in conjunction with FIG. 6.

[0048] In the FIG. 7 example, histogram 710 includes a peak 726 and apeak 730. In addition, histogram 710 also includes a peak 734(a) which“wraps around” at axis 722 (corresponding to highest theta bin 158) toinclude peak 734(b) which has counts from theta bins beginning at thetabin 1. In the FIG. 7 embodiment, theta bins corresponding to the bluerange of chromaticity angles 634 preferably begin at the higher end oftheta bins along horizontal axis 718 (the right side of histogram 710),and may, in certain instances, wrap around to include several theta binson the lower end of histogram 710 (as illustrated in the FIG. 7example). In alternate embodiments, a blue range may be located in otherappropriate locations on various similar histograms.

[0049] In certain embodiments, after theta bin histogram 710 isgenerated by color manager 416 (FIG. 4) or by any other appropriatemeans, a state machine or some other computer process preferablyexamines the “counts” in the theta bins to find the first, second, andthird largest peaks (peaks 1, 2, and 3, respectively). For example, incertain embodiments, a threshold may be set to find a new peak after thefirst peak is found. This threshold stops noisy data from giving falsepeaks. It is possible to have some special default value (like bin 0, anon-existent bin) to be the positions for peak 2 and 3 to indicate thatthere are no secondary peaks.

[0050] After the three dominant peaks are found, a series of three “IF”statements may be performed to see if peak 3 should be promoted toreplace peak 2. The purpose of this process is to find the bestpotential candidate to compare against the largest theta bin histogrampeak (always peak 1) to see which peak should be the ultimate winner. Asdiscussed above, it should be noted that as one moves to the right ofthe theta peak 730 (peak 1), the theta bin colors become more blue. Thischaracteristic is a consequence of the defining equation in which thetheta angle equals the ArcTan(b*/a*). Also note that theta is a cyclicalvariable, and after going past theta bin 158, the variable “wrapsaround” to theta bin 1 which is slightly more blue than bin 158.

[0051] In the FIG. 7 embodiment, a first “IF” condition may preferablytest whether peak 2 is to the left (i.e., has a lower theta bin number)than peak1, AND, peak 3 is to the right of peak 1. When this conditionis true, peak 3 preferably is promoted to replace peak 2. A second “IF”condition preferably tests whether peak 2 is to the right of peak 1,AND, peak 3 is to the right of peak 1. Again, when this condition istrue, peak 3 is promoted to replace peak 2, and the old peak 2 becomesthe new peak 3.

[0052] A third and last “IF” condition tests whether the potentiallynewly-promoted peak 2 is to the left of peak 1, AND, peak 1 and 2 aretwo-thirds of the way across the theta bin range, AND, peak 3 is locatedin less than the first one-third of the theta bin range. Thiscorresponds to the wrap-around condition where peaks 1 and 2 are on thefar right side of the theta bin range, and peak 3 is on the very startof the theta bin range. This means that peak 3 is more blue than peak 1.Again, when this condition is true, peak 3 is promoted to replace peak2, and the old peak 2 becomes the new peak 3.

[0053] At this point, only two peaks are still being considered, namely,peak 1 (which is always the largest “count” value in the theta binhistogram) and peak 2 (which may have recently been promoted from peak3). The default condition is that peak 1 will be considered the ultimatewinner for the neutral core chromatic vector. The next question iswhether the new peak 2 will replace peak 1 as the candidate for theultimate winner. Before continuing, a new variable is preferably definedcalled “Ratio”, which is preferably equal to the ratio of the histogramamplitudes of peak 2 divided by peak 1. When Ratio is a fractionalnumber that is less than one, in a hardware configuration, it can easilybe reconfigured to be peak1 divided by peak 2 to simplify calculations.A real division is not needed since “shifts and adds” are all that arerequired for the accuracy of Ratio to be meaningful in the followingtests.

[0054] Again, in the FIG. 7 embodiment, there are preferably three new“IF” conditions that could make peak 2 a candidate to be the ultimatewinner. The first “IF” condition preferably tests whether Ratio isgreater than or equal to 3%, AND, peak 2 is to right of peak 1, AND,both peak 1 and 2 are 2/3 of the way along the theta bin index. Thisbasically allows a small peak 2 amplitude in the very blue region on theright side of theta bin to become a candidate.

[0055] The second “IF” condition tests whether Ratio>=20%, AND, peak 2to the right of peak1. This is very much like the first “IF” conditionexcept that there are no conditions for where peaks 1 and 2 are located.In most cases, where there is a second peak, this is the “IF” conditionthat will promote peak 2 to being a candidate. It basically says that “amore blue peak than peak 1 exists and it is at least ⅕ as tall as thedominant peak” and should be considered a candidate.

[0056] The third “IF” condition preferably tests whether Ratio>=20%,AND, peak 2 is in the first ⅙ of theta bin index, AND peak 1 is in thelast ⅔ of the theta bin index. Quite simply, this is the wrap-aroundcase for peak 2 being more blue that peak 1. Again, a large amplitude ofpeak 2 is required to consider this case for peak 2 to be a candidate.

[0057] With regard to selecting the “blue-est” peak. In essence, thissays that green and red colored illuminants are common, and can mimiceach other with special filters. However, to obtain very blueilluminants in the D50 through D80 range (i.e., D5000 degrees Kelvinthrough D8000 degrees Kelvin daylight illuminance), no amount offiltering from incandescent light can give an efficient rendering ofdaylight because fluorescent and incandescent light sources have littleillumination power in the 380 to 430 nanometer wavelengths. If there issignificant deep blue content in the neutral core objects of the image,it must have come from the illuminant.

[0058] In the FIG. 7 embodiment, essentially, once the largest peak fromthe theta bins of histogram 710 is found (always called peak 1), then asearch is made of other peaks to see if one of them is more blue thanpeak 1. If such a peak is found, there are a sequence of tests based onamplitude and range of brightness that must be passed for this new peakto supersede peak 1 as the neutral core peak.

[0059] In the FIG. 7 embodiment, the final condition tests whether peak2's range is at least ½ the size of peak 1's range of brightness (i.e.,L* values). If this is the case, then peak 2 wins, and the neutral corechromaticity vector will be computed from the theta bin where peak 2 islocated. If peak 2 does not have a large range, then peak 1 is thewinner, and the chromaticity vector will be computed from the theta binbelonging to peak 1. In the FIG. 7 embodiment, once the “winner” thetabin is found, the average chromatic vector is preferably computed. TheSumL*, Suma*, and Sumb* values from that specific theta bin are dividedby the “count” value for that bin, and the aveL*, ave_a*, and ave_b*values are found. This vector may then be designated as the neutral corevector for the current image under consideration.

[0060] In the FIG. 7 embodiment, locating the neutral core vector isdescribed with reference to locating a blue-est peak on histogram 710.However, in other embodiments, peaks corresponding to other color rangesor color combinations from histogram 710 may alternately be utilized asa references to locate an appropriate neutral core vector.

[0061] Referring now to FIG. 8, a graph illustrating a neutral core (NC)vector 814 and two reference vectors 818(a) and 818(b) inthree-dimensional perceptual color space 810 is shown, in accordancewith one embodiment of the present invention. In alternate embodiments,the present invention may readily utilize NC vectors and referencevectors that are implemented in various other color spaces, and may alsoinclude various elements, vectors, and configurations that are differentfrom those discussed in conjunction with the FIG. 8 embodiment.

[0062] For example, although the FIG. 8 embodiment utilizes only tworeference vectors 818 for purposes of clarity, in many embodiments, thepresent invention may typically compare NC vector 814 to a significantlylarger number of reference vectors 818. For instance, reference vectors818 may represent various illuminants that include, but are not limitedto, D65 (midafternoon sunlight with slight overcast [6500 degreesKelvin]), D50 (noonday sunlight [5000 degrees Kelvin]), U30 (fluorescentlighting), 3200 (studio floodlights [3200 degrees Kelvin]), A (tungstenincandescent lighting), and horizon (late afternoon sunlight).

[0063] In accordance with certain embodiments, color manager 416 oranother appropriate entity may preferably compare NC vector 814 (asdescribed above in conjunction with FIG. 7) with known reference vectors818 to identify a closest matching reference vector. In the FIG. 8embodiment, color manager 416 may preferably calculate tau angles 826(a)and 826(b) between NC vector 814 and respective reference vectors 818(a)and 818(b) to thereby identify the reference vector 818 corresponding tothe smallest tau angle 826 as the scene illuminant associated with NCvector 814.

[0064] In the FIG. 8 embodiment, reference vector 1 (818(a)) correspondsto the smallest tau angle 1 (826(a)). In certain embodiments, thepresent invention may interpolate between two or more of the referencevectors 818 with the smallest tau angles 826, as discussed below. In theFIG. 8 embodiment, color manager 416 may then preferably referenceamplifier gain lookup tables to determine known gain values (such as B/Gand R/G values) for the identified illuminant, and may advantageouslythe adjust the respective gains of R/G/B amplifiers 228 (FIGS. 2 and 5)to complete the white balance operation.

[0065] Referring now to FIG. 9, a flowchart of method steps forperforming a basic neutral-core white-balance operation is shown, inaccordance with one embodiment of the present invention. The FIG. 9embodiment is presented for purposes of illustration, and in alternateembodiments, the present invention may readily utilize various othersteps and sequences than those discussed in conjunction with the FIG. 9embodiment.

[0066] In the FIG. 9 embodiment, in step 912, a color manager 416 orother appropriate entity may preferably decimate the pixels of capturedimage data to reduce the overall number of pixels by utilizing anyappropriate and effective technique. For example, color manager 416 mayexclude every “nth” pixel from the capture image data. In the FIG. 9embodiment, the decimated image data may preferably retain in the rangeof slightly over 1000 pixels, however, in other embodiments, thedecimated image data may include any suitable number of pixels. Incertain embodiments, in step 912, pixels with values under apre-determined threshold value may also be eliminated.

[0067] In step 916, color manager 416 or other appropriate entity maypreferably convert the foregoing decimated pixels into a perceptualcolor space. For example, color manager 416 may convert the decimatedpixels into a three-dimensional perceptual color space that includes oneluminance coordinate and two color coordinates, such L*a*b* color space,or into any other suitable and effective color space.

[0068] In step 920, color manager 416 or other appropriate entity maypreferably calculate chromaticity vectors 634 for each pixel from theperceptual color space, and may then preferably histogram the foregoingchromaticity vectors 634 into a series of contiguous theta bins that maybe presented as a histogram 710 with one or more peaks eachcorresponding to total counts of the chromaticity vectors 634 in theforegoing theta bins.

[0069] In step 926, color manager 416 or other appropriate entity maypreferably identify a neutral core peak 734 from histogram 710 byutilizing any effective techniques. For example, in the FIG. 9embodiment, color manager 416 may preferably identify the foregoingneutral core peak 743 as the “blue-est” peak in the blue region of thetabins of histogram 710 that possesses sufficient count amplitude andluminance range.

[0070] In step 928, color manager 416 or other appropriate entity maypreferably derive a neutral core vector 814 from data valuescorresponding to the foregoing neutral core peak 734 from histogram 710by utilizing any appropriate techniques. For example, in the FIG. 9embodiment, color manager 416 may preferably calculate averages of L*,a*, and b* values for all chromaticity vectors 634 in the theta bin(s)corresponding to the neutral core peak 734 to determine the L*a*b*coordinates of neutral core vector 814.

[0071] In step 932, color manager 416 or other appropriate entity maypreferably compare the neutral core vector 814 with reference vectors818 from various known standard illuminants to identify the sceneilluminant corresponding to the captured image data. Finally, in step936, color manager 416 or other appropriate entity may preferably accesscolor amplifier gains for primary color channels 228 of camera device110 based upon the identified scene illuminant by using any appropriatemeans. For example, color manager 416 may reference one or more lookuptables with the identified scene illuminant to determine the correctcolor amplifier gains for that illuminant. Color manager 416 or otherappropriate entity may then preferably utilize the referenced coloramplifier gains to adjust the gains of primary color channels 228, tothereby complete the white balance operation in accordance with thepresent invention.

[0072] The FIG. 9 embodiment is disclosed and discussed in the contextof a digital still camera. However, in alternate embodiments, thepresent invention may readily be embodied in a computer device or anyother type of electronic device that accesses and compensates forwhite-balance deviations in captured image data by utilizing theprinciples and techniques of the present invention.

[0073] Referring now to FIGS. 10A-D, a flowchart of method steps forperforming a detailed neutral-core white-balance operation is shown, inaccordance with one embodiment of the present invention. The FIGS. 10A-Dembodiment is presented for purposes of illustration, and in alternateembodiments, the present invention may readily utilize various othersteps and sequences than those discussed in conjunction with the FIGS.10A-D embodiment. In FIGS. 10A-10D, a logical AND function may beexpressed by the symbol “&&” which indicates that all specifiedconditions must be simultaneously true for the IF statement to be true.Furthermore, in the discussion of FIGS. 10A-10D and elsewhere in thisdocument, the foregoing logical AND function may be expressed by thecapitalized word “AND”.

[0074] In the FIG. 10A embodiment, in step 1, a color manager 416 oranother appropriate entity may preferably perform a demosaicingprocedure upon a set of Red/Green/Blue (RGB) image data to generate orinterpolate separate red, green, and blue values for each pixel byutilizing any effective technique. In other embodiments, the capturedimage data may be encoded in any other suitable format. For example,C/M/Y/G, which could then be reduced into a 3-color primary system, likeR/G/B. In step 1, color manager 416 or another appropriate entity mayalso preferably perform a subsampling procedure to decimate the numberof pixels in the captured image data, as discussed above in conjunctionwith FIG. 9.

[0075] In step 2, color manager 416 or another appropriate entity maypreferably remove all pixels with a red value less than 15, AND a greenvalue less than 15, AND a blue (B) value less than 15 from thedemosaiced and subsampled image data. In other embodiments the thresholdvalue of 15 may be implemented as any other effective threshold value.In step 3, color manager 416 or another appropriate entity maypreferably convert the foregoing processed image data into a perceptualcolor space, such as L*a*b*, as discussed above in conjunction with FIG.9.

[0076] In step 4, color manager 416 or another appropriate entity maypreferably remove all pixels with a luminance (L*) value less than 15from the perceptual color space data. Then, in step 5, color manager 416or another appropriate entity may preferably histogram the selectedperceptual color space pixels into theta bins, as discussed above inconjunction with FIGS. 69. In step 5, color manager 416 or anotherappropriate entity may also save a minimum luminance (minL*) and amaximum luminance (maxL*) count for each theta bin from histogram 710for subsequently calculating a luminance range value for each theta bin.

[0077] In step 5 a, color manager 416 or another appropriate entity maypreferably perform a two-step moving average on peak values fromneighboring theta bins to interpolate additional values and therebysmooth peaks in histogram 710. In step 6, color manager 416 or anotherappropriate entity may preferably locate the three largest peaks inhistogram 710. In addition, color manager 416 or another appropriateentity may label the located peaks as m1p, m2p, and m3p to correspond totheir relative positions in histogram 710, and may also label thelocated peaks as m1v, m2v, and m3v to correspond to their respectiveamplitudes or histogram counts. The FIG. 10A flowchart may then connectto letter “A” (step 7) of the FIG. 10B flowchart.

[0078] In step 7 of the FIG. 10B embodiment, color manager 416 oranother appropriate entity may preferably determine whether m2p is lessthan m1p AND m3p is greater than m1p. If the conditions of step 7 aretrue, then in step 8, color manager 416 or another appropriate entitymay preferably promote peak 3 to peak 2 (set m2p equal to m3p, and setm2v equal to m3v) because peak m3p is to the right (more blue) of peakm1p, and peak m2p is left of peak m1p.

[0079] Next, in step 9, color manager 4 6 or another appropriate entitymay preferably determine whether m2p is greater than m1p, AND m3p isgreater than m2p, AND a shoulder condition exists in which m3p must begreater than a shoulder threshold value of m2p. These “shoulder”conditions pertain to all placements of peaks relative to one another,when the promotion of a peak is being considered. If the conditions ofstep 9 are true, then in step 10, color manager 416 or anotherappropriate entity may preferably promote peak 3 to peak 2 (set m2pequal to m3p, and set m2v equal to m3v) because peak m3p is to the right(more blue) of both other peaks, and peak m1p is on the right side ofhistogram 710.

[0080] Next, in step 11, color manager 416 or another appropriate entitymay preferably determine whether m2p is less than m1p, AND a relativelybright luminance condition exists, AND m3p is less than the number oftheta bins divided by 3. If the conditions of step 11 are true, then instep 12, color manager 416 or another appropriate entity may preferablypromote peak 3 to peak 2 (set m2p equal to m3p, and set m2v equal tom3v) because peaks m1p and m2p are on extreme right of histogram 710,and peak m3p is on the extreme left side (most blue) of histogram 710.The FIG. 10B flowchart may then connect to letter “B” (step 13 a) of theFIG. 10C flowchart.

[0081] In step 13 a of the FIG. 10C flowchart, color manager 416 oranother appropriate entity may preferably set a Ratio equal to thecurrent value of m1v divided by the current value of m2v, as discussedabove in conjunction with FIG. 6. Then, in step 13 b, color manager 416or another appropriate entity may preferably determine whether theforegoing Ratio is greater than or equal to 0.03, AND m2p is greaterthan m1p, AND a relatively bright luminance condition exists. If theconditions of step 13 b are true, then in step 14, color manager 416 oranother appropriate entity may preferably identify peak m2p as theneutral core peak candidate, because there is a small peak m2p to theright of peak m1p, and both peaks m1p and m2p are on far right ofhistogram 710. However, the selection may be disallowed if peak m2p isat the extreme right of histogram 710.

[0082] Next, in step 15, color manager 416 or another appropriate entitymay preferably determine whether the foregoing Ratio is greater than orequal to 0.20, AND m2p is greater than m1p. If the conditions of step 15are true, then in step 16, color manager 416 or another appropriateentity may preferably identify peak m2p as the neutral core peakcandidate, because there is a large peak m2p to the right of peak m1p.The selection may be allowed even if peak m2p is at the extreme right ofhistogram 710.

[0083] In step 17, color manager 416 or another appropriate entity maypreferably determine whether the foregoing Ratio is greater than orequal to 0.20, AND m2p is less than the number of theta bins divided by6, AND m1p is greater than the number of theta bins times two-thirds. Ifthe conditions of step 17 are true, then in step 18, color manager 416or another appropriate entity may preferably promote peak m3p to peakm2p, and then may preferably identify the new peak m2p as the neutralcore peak candidate, because there is a large peak m2p on the far rightof histogram 710, and peak m1p is on far left side of histogram 710 in a“wrap-around” condition. The FIG. 10C flowchart may then connect toletter “C” (step 19) of the FIG. 10D flowchart.

[0084] In step 19 of the FIG. 10D flowchart, color manager 416 oranother appropriate entity may preferably determine whether peak m2p haspreviously been identified as the neutral core peak candidate, AND theluminance range of peak m2p is greater than or equal to 0.5 times therange of peak m1p. If the conditions in step 19 are satisfied, then instep 20, color manager 416 or another appropriate entity may preferablymake a final determination that peak m2p is identified as the neutralcore peak. Color manager 416 or another appropriate entity may thencalculate averages, aveL*, ave_a*, and ave_b*, from stored elements inthe theta bin for peak m2p to define coordinates for a neutral corevector 814.

[0085] However, if the conditions in step 19 are not satisfied, then instep 21, color manager 416 or another appropriate entity may preferablymake a final determination that peak m1p is identified as the neutralcore peak. Color manager 416 or another appropriate entity may thencalculate averages, aveL*, ave_a*, and ave_b*, from stored elements inthe theta bin for peak m1p to define coordinates for a neutral corevector 814. In step 22, color manager 416 or another appropriate entitymay preferably compute a tau angle 826 between each reference vector 818and the foregoing neutral core vector 814.

[0086] In step 24, color manager 416 or another appropriate entity maypreferably identify the reference vector 818 with the smallest tau angle826 as the scene illuminant for the captured image data. In the FIG. 10Dembodiment, color manager 416 or another appropriate entity maypreferably utilize the two smallest tau angles 826 to interpolate aCorrelated Color Temperature (CCT) for the identified scene illuminant.In step 25, color manager 416 or another appropriate entity maypreferably perform a table lookup procedure for the CCT to obtainstandard amplifier gains for the particular scene illuminant. Colormanager 416 or another appropriate entity may then adjust the amplifiergains of primary color channels 228 in accordance with the standardamplifier gains to complete the white balance operation.

[0087] The invention has been explained above with reference to certainembodiments. Other embodiments will be apparent to those skilled in theart in light of this disclosure. For example, the present invention mayreadily be implemented using configurations and techniques other thanthose described in the embodiments above. Additionally, the presentinvention may effectively be used in conjunction with systems other thanthose described above. Therefore, these and other variations upon thediscussed embodiments are intended to be covered by the presentinvention, which is limited only by the appended claims.

What is claimed is:
 1. A system for efficiently performing a white balancing operation, comprising: an imaging device configured to provide captured image data corresponding to a photographic image; and a color manager configured to convert said captured image data into perceptual color space data, said color manager creating a histogram of chromaticity vectors corresponding to said perceptual color space data, said color manager next deriving a neutral core vector corresponding to a neutral core peak from said histogram, said color manager utilizing said neutral core vector to identify a scene illuminant corresponding to color channel amplifier gains, said color manager then adjusting said captured image data with said color channel amplifier gains to thereby complete said white balancing operation.
 2. The system of claim 1 wherein said imaging device and said color manager are implemented as part of an electronic camera device.
 3. The system of claim 1 wherein said color manager decimates said captured image data to reduce a pixel total for said captured image data, said color manager then converting said captured image data into said perceptual color space data.
 4. The system of claim 1 wherein said color manager identifies said chromaticity vectors by calculating theta angles which define color characteristics of pixels in said perceptual color space data, said color manager then creating said histogram by defining theta bins which each store chromaticity vector counts that correspond to different theta angles of said chromaticity vectors, said histogram plotting a sequence of said theta bins versus said chromaticity vector counts.
 5. The system of claim 1 wherein said color manager identifies said neutral core peak from said histogram by determining appropriate chromaticity characteristics for said neutral core peak, said color manager calculating said neutral core vector by averaging luminance coordinates and color coordinates for said chromaticity vectors that correspond to said neutral core peak.
 6. The system of claim 1 wherein said color manager analyzes said histogram to locate a maximum blue chromaticity region which corresponds to an optimal location for said neutral core peak, said color manager identifying a candidate peak which is closest to said maximum blue chromaticity region as said neutral core peak.
 7. The system of claim 1 wherein said color manager compares said neutral core vector with reference vectors corresponding to known standard illuminants to thereby identify said scene illuminant, said color manager calculating theta angles between said neutral core vector and each of said reference vectors, said scene illuminant corresponding to one of said reference vectors with a smallest one of said theta angles.
 8. The system of claim 1 wherein said color manager accesses said color channel amplifier gains corresponding to said scene illuminant by referencing a lookup table, said color manager adjusting primary color channels of said imaging device with said color channel amplifier gains to thereby complete said white balancing operation.
 9. The system of claim 1 wherein said color manager performs a demosaicing procedure upon a set of Red/Green/Blue (RGB) image data to interpolate separate red, green, and blue values for each pixel location, said color manager also performing a subsampling procedure to decimate a pixel total in said captured image data.
 10. The system of claim 9 wherein said color manager removes RGB pixels with a red value less than 15, and a green value less than 15, and a blue (B) value less than 15 from said captured image data.
 11. The system of claim 10 wherein said color manager converts said captured image data into said perceptual color space data which is configured in an L*a*b* format.
 12. The system of claim 11 wherein said color manager removes perceptual color space pixels with a luminance (L*) value that is less than 15 from said perceptual color space data.
 13. The system of claim 12 wherein said color manager creates said histogram by calculating said chromaticity vectors, said color manager then histogramming said perceptual color space pixels into theta bins according to theta angles of said chromaticity vectors.
 14. The system of claim 13 wherein said color manager saves a minimum luminance (minL*) and a maximum luminance (maxL*) count for each of said theta bins from said histogram for subsequently calculating a luminance range value for said each of said theta bins.
 15. The system of claim 14 wherein said color manager performs a two-step moving average on peak values from neighboring theta bins to interpolate additional values and thereby smooth adjacent peaks in said histogram.
 16. The system of claim 15 wherein said color manager identifies three largest peaks in said histogram as peak 1, peak 2, and peak
 3. 17. The system of claim 16 wherein said color manager labels said three largest peaks as m1p, m2p, and m3p to correspond to their relative positions in said histogram, said color manager also labeling said three largest peaks as m1v, m2v, and m3v to correspond to their respective amplitudes.
 18. The system of claim 17 wherein said color manager performs a first promotion procedure by promoting said peak 3 to become said peak 2, which sets m2p equal to m3p, and which sets m2v equal to m3v, said color manager performing said first promotion procedure whenever m2p is less than m1p, and m3p is greater than m1p.
 19. The system of claim 18 wherein said color manager performs a second promotion procedure by promoting said peak 3 to become said peak 2, which sets m2p equal to m3p, and which sets m2v equal to m3v, said color manager performing said second promotion procedure whenever m2p is greater than m1p, and m3p is greater than m2p, and a shoulder condition exists in which a blue peak wraps around from the highest end of said histogram to a lowest end of said histogram.
 20. The system of claim 19 wherein said color manager performs a third promotion procedure to promote said peak 3 to said peak 2, which sets m2p equal to m3p, and which sets m2v equal to m3v, said color manager performing said third promotion procedure whenever m2p is less than m1p, and a first relatively bright luminance condition exists, and m3p is less than a total number of said theta bins divided by
 3. 21. The system of claim 20 wherein said color manager calculates a ratio to be equal to a current value of m1v divided by a current value of m2v.
 22. The system of claim 21 wherein said color manager identifies said peak 2 as a neutral core peak candidate whenever said ratio is greater than-or equal to 0.03, and m2p is greater than m1p, and a second relatively bright luminance condition exists.
 23. The system of claim 22 wherein said color manager identifies said peak 2 as said neutral core peak candidate whenever said ratio is greater than or equal to 0.20, and m2p is greater than m1p.
 24. The system of claim 23 wherein said color manager promotes said peak 3 to become said peak 2, and then identifies said peak 2 as said neutral core peak candidate, whenever said ratio is greater than or equal to 0.20, and m2p is less than a total number of said theta bins divided by 6, and m1p is greater than said total number of said theta bins times two-thirds.
 25. The system of claim 24 wherein said color manager performs a final determination procedure to indicate that said peak 2 is identified as said neutral core peak, said color manager then calculating averages, aveL*, ave_a*, and ave_b*, from stored elements in a peak 2 theta bin for said peak 2 to define coordinates for said neutral core vector, said color manager performing said first final determination procedure whenever said peak 2 has previously been identified as said neutral core peak candidate, and a first luminance range of said peak 2 is greater than or equal to 0.5 times a second luminance range of said peak
 1. 26. The system of claim 24 wherein said color manager performs said final determination procedure to indicate that said peak 1 is identified as said neutral core peak, said color manager then calculating said averages, aveL*, ave_a*, and ave_b*, from said stored elements in a peak 1 theta bin for said peak 1 to define said coordinates for said neutral core vector, said color manager performing said final determination procedure whenever said peak 2 has not previously been identified as said neutral core peak candidate, or whenever said first luminance range of said peak 2 is not greater than or equal to 0.5 times said second luminance range of said peak
 1. 27. The system of claim 26 wherein said color manager computes tau angles between reference vectors for known illuminants and said neutral core vector.
 28. The system of claim 27 wherein said color manager identifies a scene illuminant reference vector with a smallest tau angle as said scene illuminant for said captured image data.
 29. The system of claim 28 wherein said color manager utilizes two smallest ones of said tau angles to interpolate a correlated color temperature for said scene illuminant.
 30. The system of claim 29 wherein said color manager performs a table lookup procedure for said correlated color temperature to obtain said color channel amplifier gains for said scene illuminant, said color manager then adjusting amplifier gains of primary color channels in accordance with said color channel amplifier gains to complete said white balancing operation.
 31. A method for efficiently performing a white balancing operation, comprising the steps of: providing captured image data from an imaging device, said captured image data corresponding to a photographic image; converting said captured image data into perceptual color space data; creating a histogram of chromaticity vectors corresponding to said perceptual color space data by utilizing a color manager; deriving a neutral core vector corresponding to a neutral core peak from said histogram by utilizing said color manager; utilizing said neutral core vector to identify a scene illuminant corresponding to color channel amplifier gains; and adjusting said captured image data with said color channel amplifier gains to thereby complete said white balancing operation.
 32. The method of claim 31 wherein said imaging device and said color manager are implemented as part of an electronic camera device.
 33. The method of claim 31 wherein said color manager decimates said captured image data to reduce a pixel total for said captured image data, said color manager then converting said captured image data into said perceptual color space data.
 34. The method of claim 31 wherein said color manager identifies said chromaticity vectors by calculating theta angles which define color characteristics of pixels in said perceptual color space data, said color manager then creating said histogram by defining theta bins which each store chromaticity vector counts that correspond to different theta angles of said chromaticity vectors, said histogram plotting a sequence of said theta bins versus said chromaticity vector counts.
 35. The method of claim 31 wherein said color manager identifies said neutral core peak from said histogram by determining appropriate chromaticity characteristics for said neutral core peak, said color manager calculating said neutral core vector by averaging luminance coordinates and color coordinates for said chromaticity vectors that correspond to said neutral core peak.
 36. The method of claim 31 wherein said color manager analyzes said histogram to locate a maximum blue chromaticity region which corresponds to an optimal location for said neutral core peak, said color manager identifying a candidate peak which is closest to said maximum blue chromaticity region as said neutral core peak.
 37. The method of claim 31 wherein said color manager compares said neutral core vector with reference vectors corresponding to known standard illuminants to thereby identify said scene illuminant, said color manager calculating theta angles between said neutral core vector and each of said reference vectors, said scene illuminant corresponding to one of said reference vectors with a smallest one of said theta angles.
 38. The method of claim 31 wherein said color manager accesses said color channel amplifier gains corresponding to said scene illuminant by referencing a lookup table, said color manager adjusting primary color channels of said imaging device with said color channel amplifier gains to thereby complete said white balancing operation.
 39. The method of claim 31 wherein said color manager performs a demosaicing procedure upon a set of color primary image data, including at least three color channels, to interpolate separate color primary values for each pixel location, said color manager also performing a subsampling procedure to decimate a pixel total in said captured image data.
 40. The method of claim 39 wherein said color manager removes RGB pixels with a red value less than approximately 15, and a green value less than approximately 15, and a blue (B) value less than approximately 15 from said captured image data.
 41. The method of claim 40 wherein said color manager converts said captured image data into said perceptual color space data which is configured in an L*a*b* format.
 42. The method of claim 41 wherein said color manager removes perceptual color space pixels with a luminance (L*) value that is less than approximately 15 from said perceptual color space data.
 43. The method of claim 42 wherein said color manager creates said histogram by calculating said chromaticity vectors, said color manager then histogramming said perceptual color space pixels into theta bins according to theta angles of said chromaticity vectors.
 44. The method of claim 43 wherein said color manager saves a minimum luminance (minL*) and a maximum luminance (maxL*) count for each of said theta bins from said histogram for subsequently calculating a luminance range value for said each of said theta bins.
 45. The method of claim 44 wherein said color manager performs a data smoothing process on peak values from neighboring theta bins to interpolate additional values and thereby smooth adjacent peaks in said histogram.
 46. The method of claim 45 wherein said color manager identifies three largest peaks in said histogram as peak 1, peak 2, and peak
 3. 47. The method of claim 46 wherein said color manager labels said three largest peaks as m1p, m2p, and m3p to correspond to their relative positions in said histogram, said color manager also labeling said three largest peaks as m1v, m2v, and m3v to correspond to their respective amplitudes.
 48. The method of claim 47 wherein said color manager performs a first promotion procedure by promoting said peak 3 to become said peak 2, which sets m2p equal to m3p, and which sets m2v equal to m3v, said color manager performing said first promotion procedure whenever m2p is less than m1p, and m3p is greater than m1p.
 49. The method of claim 48 wherein said color manager performs a second promotion procedure by promoting said peak 3 to become said peak 2, which sets m2p equal to m3p, and which sets m2v equal to m3v, said color manager performing said second promotion procedure whenever m2p is greater than m1p, and m3p is greater than m2p, and a shoulder condition exists in which a blue peak wraps around from the highest end of said histogram to a lowest end of said histogram.
 50. The method of claim 49 wherein said color manager performs a third promotion procedure to promote said peak 3 to said peak 2, which sets m2p equal to m3p, and which sets m2v equal to m3v, said color manager performing said third promotion procedure whenever m2p is less than m1p, and a first relatively bright luminance condition exists, and m3p is less than a total number of said theta bins divided by approximately
 3. 51. The method of claim 50 wherein said color manager calculates a ratio to be equal to a current value of m1v divided by a current value of m2v.
 52. The method of claim 51 wherein said color manager identifies said peak 2 as a neutral core peak candidate whenever said ratio is greater than or equal to approximately 0.03, and m2p is greater than m1p, and a second relatively bright luminance condition exists.
 53. The method of claim 52 wherein said color manager identifies said peak 2 as said neutral core peak candidate whenever said ratio is greater than or equal to approximately 0.20, and m2p is greater than m1p.
 54. The method of claim 53 wherein said color manager promotes said peak 3 to become said peak 2, and then identifies said peak 2 as said neutral core peak candidate, whenever said ratio is greater than or equal to approximately 0.20, and m2p is less than a total number of said theta bins divided by approximately 6, and m1p is greater than said total number of said theta bins times approximately two-thirds.
 55. The method of claim 54 wherein said color manager performs a final determination procedure to indicate that said peak 2 is identified as said neutral core peak, said color manager then calculating averages, aveL*, ave_a*, and ave_b*, from stored elements in a peak 2 theta bin for said peak 2 to define coordinates for said neutral core vector, said color manager performing said first final determination procedure whenever said peak 2 has previously been identified as said neutral core peak candidate, and a first luminance range of said peak 2 is greater than or equal to approximately 0.5 times a second luminance range of said peak
 1. 56. The method of claim 55 wherein said color manager performs said final determination procedure to indicate that said peak 1 is identified as said neutral core peak, said color manager then calculating said averages, aveL*, ave_a*, and ave_b*, from said stored elements in a peak 1 theta bin for said peak 1 to define said coordinates for said neutral core vector, said color manager performing said final determination procedure whenever said peak 2 has not previously been identified as said neutral core peak candidate, or whenever said first luminance range of said peak 2 is not greater than or equal to approximately 0.5 times said second luminance range of said peak
 1. 57. The method of claim 56 wherein said color manager computes tau angles between reference vectors for known illuminants and said neutral core vector.
 58. The method of claim 57 wherein said color manager identifies a scene illuminant reference vector with a smallest tau angle as said scene illuminant for said captured image data.
 59. The method of claim 58 wherein said color manager utilizes two smallest ones of said tau angles to interpolate a correlated color temperature for said scene illuminant.
 60. The method of claim 59 wherein said color manager performs a table lookup procedure for said correlated color temperature to obtain said color channel amplifier gains for said scene illuminant, said color manager then adjusting amplifier gains of primary color channels in accordance with said color channel amplifier gains to complete said white balancing operation.
 61. A computer-readable medium comprising program instructions for performing a white balancing operation by performing the steps of: providing captured image data from an imaging device, said captured image data corresponding to a photographic image; converting said captured image data into perceptual color space data; creating a histogram of chromaticity vectors corresponding to said perceptual color space data by utilizing a color manager; deriving a neutral core vector corresponding to a neutral core peak from said histogram by utilizing said color manager; utilizing said neutral core vector to identify a scene illuminant corresponding to color channel amplifier gains; and adjusting said captured image data with said color channel amplifier gains to thereby complete said white balancing operation.
 62. A system for efficiently performing a white balancing operation, comprising: means for providing captured image data corresponding to a photographic image; means for converting said captured image data into perceptual color space data; means for creating a histogram of chromaticity vectors corresponding to said perceptual color space data; means for deriving a neutral core vector corresponding to a neutral core peak from said histogram; means for utilizing said neutral core vector to identify a scene illuminant corresponding to color channel amplifier gains; and means for adjusting said captured image data with said color channel amplifier gains to thereby complete said white balancing operation.
 63. A system for efficiently performing a white balancing operation, comprising: means for providing captured image data corresponding to a photographic image; and a color manager configured to derive a neutral core vector corresponding for said captured image data, said color manager utilizing said neutral core vector to identify a scene illuminant for adjusting said captured image data to thereby complete said white balancing operation. 